期刊
COMPUTERS IN BIOLOGY AND MEDICINE
卷 159, 期 -, 页码 -出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.compbiomed.2023.106898
关键词
Neural network; Lumped parameter model; REBOA; 1D model
Based on the generalized Darcy model, a linear one-dimensional (1D) composite model is developed to predict the effects of the inserted balloon on blood flow dynamics in flexible arterial networks during REBOA operations. The model considers the decrease of cardiac output under different degrees of blood loss and incorporates the effect of the inserted balloon using a neural network approach. The accuracy of the 1D composite model is verified through comparison with computational fluid dynamics simulations and it is proven to reproduce the main features of the systemic circulation under balloon occlusion during REBOA surgery. The model's ability to provide instant predictions of working parameters during RABOA operations is particularly valuable.
Based on the generalized Darcy model, here we develop a linear one-dimensional (1D) composite model to predict the effects of the inserted balloon under REBOA operations on the dynamic characteristics of blood flow in flexible arterial networks. We first consider the effect of the decrease of cardiac output under different degrees of blood loss through employing the fourth-order lumped parameter model of cardiovascular system. Then, the effect of the inserted balloon is included by developing the relation between flow resistance and occlusion ratio with the neural network approach. Finally, the accuracy of the developed 1D composite model for REBOA operations, which can be solved analytically in the frequency domain, is verified by comparing to computational fluid dynamics (CFD) simulations. It is demonstrated that the 1D model is able to reproduce main features of the systemic circulation under balloon occlusion of the aorta during REBOA surgery. The 1D composite model could substantially reduce the computational time, which makes it possible to give the instant prediction of the working parameters during RABOA operations.
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